TECHNICAL FIELD
[0001] Various examples generally relate to tracking sound exposure. Various examples specifically
relate to determining a cumulative sound-exposure dose.
BACKGROUND
[0002] Exposure to sound can cause damages to the human ear. Accordingly, there have been
efforts to track the sound-exposure dose so as to provide a warning when required.
[0003] For example, a dosimeter as specified in WHO/ITU-T H.870 determines a cumulative
sound-exposure dose based on a combination of multiple sound-exposure doses over the
past days. See Rec. ITU-T H.870 (08/2018), section II.7 "dosimeter implementation
example". A warning is triggered if this cumulative sound-exposure dose exceeds a
predefined threshold.
[0004] EP 2 333 497 A1 discloses a method for controlling the cumulated audio dose of a user of a media
player.
US 2017/374444 A1 discloses methods and apparatuses for user sound exposure limiting.
US 2015/110276 A1 discloses a method for source selective real-time monitoring and mapping of environmental
noise.
[0005] It has been found that such reference techniques of tracking the sound exposure can
result in a high number of warnings and be subject to volatility. Inaccurate warnings
have been observed.
Summary
[0006] Accordingly, there is a need for advanced techniques of tracking exposure to sound.
There is a need for techniques that alleviate or mitigate the above-identified drawbacks.
[0007] This need is met by the features of the independent claims. The features of the dependent
claims define embodiments.
[0008] A method includes determining multiple sound-exposure doses. Each sound-exposure
dose is determined for a respective time interval of multiple time intervals of a
discretized and rolling sequence of time intervals. The method also includes determining
a cumulative sound-exposure dose based on a combination of the multiple sound-exposure
doses. The combination includes a weighted contribution of the sound-exposure dose
of at least one earliest time interval of the sequence of time intervals. The at least
one earliest time interval includes multiple earliest time intervals of the rolling
sequence of time intervals. A respective weighted contribution for each of the multiple
earliest time intervals comprises a different weighting factor smaller than 1 and
larger than 0. The respective weighting factor is time dependent. The respective weighting
factor changes from 1 to 0 as time progresses from a beginning of a respective time
interval to an end of the respective time interval. The weighted contribution is based
on an average of the multiple earliest time intervals forming the at least one earliest
time interval. The method further comprises in response to the cumulative sound-exposure
dose crossing a predefined threshold, selectively triggering a warning.
[0009] The techniques described herein facilitate an accurate determination of the cumulative
sound-exposure dose. In particular, quantization effects observed in reference implementations
due to the consideration of multiple time intervals of the rolling sequence can be
mitigated. In reference implementations, fluctuations of the cumulative sound-exposure
dose are observed and unnecessary warnings can be triggered. Such problems are mitigated
by using the weighted contribution of the sound-exposure dose of the at least one
earliest time interval.
[0010] It is to be understood that the features mentioned above and those yet to be explained
below may be used not only in the respective combinations indicated, but also in other
combinations or in isolation without departing from the scope of the disclosure.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011]
FIG. 1 schematically illustrates a device according to various examples configured
to track sound exposure.
FIG. 2 schematically illustrates a device according to various examples configured
to track sound exposure.
FIG. 3 is a flowchart of a method according to various examples.
FIG. 4 schematically illustrates determining acoustic doses for multiple time intervals
of a sequence of time intervals .
FIG. 5 schematically illustrates determining a cumulative sound-exposure dose based
on a combination of sound-exposure doses of multiple time intervals, both according
to reference techniques, as well as according to various examples.
FIG. 6 is a flowchart of a method according to various examples.
FIG. 7 schematically illustrates a time-dependency of an acoustic level of a simulation
that illustrates effects of various examples described herein.
FIG. 8 also schematically illustrates the time-dependency of the acoustic level and
weekly dose of the simulation, considering an adjustment in the user behavior in response
to a warning triggered based on a cumulative sound-exposure dose.
FIG. 9 schematically illustrates quantization effects in the cumulative sound-exposure
dose determined according to reference implementations
DETAILED DESCRIPTION OF EMBODIMENTS
[0012] Some examples of the present disclosure generally provide for a plurality of circuits
or other electrical devices. All references to the circuits and other electrical devices
and the functionality provided by each are not intended to be limited to encompassing
only what is illustrated and described herein. While particular labels may be assigned
to the various circuits or other electrical devices disclosed, such labels are not
intended to limit the scope of operation for the circuits and the other electrical
devices. Such circuits and other electrical devices may be combined with each other
and/or separated in any manner based on the particular type of electrical implementation
that is desired. It is recognized that any circuit or other electrical device disclosed
herein may include any number of microcontrollers, a graphics processor unit (GPU),
integrated circuits, memory devices (e.g., FLASH, random access memory (RAM), read
only memory (ROM), electrically programmable read only memory (EPROM), electrically
erasable programmable read only memory (EEPROM), or other suitable variants thereof),
and software which co-act with one another to perform operation(s) disclosed herein.
In addition, any one or more of the electrical devices may be configured to execute
a program code that is embodied in a non-transitory computer readable medium programmed
to perform any number of the functions as disclosed.
[0013] In the following, embodiments will be described in detail with reference to the accompanying
drawings. It is to be understood that the following description of embodiments is
not to be taken in a limiting sense. The scope is not intended to be limited by the
embodiments described hereinafter or by the drawings, which are taken to be illustrative
only.
[0014] The drawings are to be regarded as being schematic representations and elements illustrated
in the drawings are not necessarily shown to scale. Rather, the various elements are
represented such that their function and general purpose become apparent to a person
skilled in the art. Any connection or coupling between functional blocks, devices,
components, or other physical or functional units shown in the drawings or described
herein may also be implemented by an indirect connection or coupling. A coupling between
components may also be established over a wireless connection. Functional blocks may
be implemented in hardware, firmware, software, or a combination thereof.
[0015] Hereinafter, techniques that facilitate an audio dosimeter functionality are described.
I.e., techniques are described that facilitate determining a sound-exposure dose.
In particular, techniques are described that facilitate determining a cumulative sound-exposure
dose (CSD) that takes into account the sound exposure observed in multiple time intervals.
For instance, the sound-exposure doses of multiple time intervals can be combined,
e.g., averaged or summed.
[0016] As a general rule, the sound-exposure dose of a given time interval can be determined
by aggregating/integrating the acoustic power in that given time interval over the
course of time t. This aggregation of acoustic power yields an acoustic energy. The
acoustic energy correlates with the dose. This is described by Eq. (0) below:

where
pA is the A-weighted and diffuse-field corrected sound pressure and the squared sound
pressure correlates with the acoustic power. Eq. (0) implements the aggregation of
the acoustic power by means of a time integration between points in time t1 and t2,
to yield an acoustic energy associated with sound-exposure dose.
[0017] The sound pressure can also be determined based on the acoustic/sound level. Note
that such A-weighting and diffuse-field corrections are generally optional; no or
other pre-processing of the sound pressure or acoustic power would be conceivable.
[0018] As a general rule, the term acoustic power is used herein for the square of sound
pressure at a given point in space (i.e., not integrated over all solid angles) and
the term acoustic energy is used for the time-integrated acoustic power or more generally
the (time-)aggregated acoustic power. Note that the acoustic energy itself can be
aggregated over multiple sampling intervals, by adjusting the sound-exposure dose
as time progresses: As time progresses, more and more acoustic energy accumulates;
the sound-exposure dose increases.
[0019] For example, the CSD could be determined based on the sound-exposure doses of multiple
days, e.g., the last 7 days, or for multiple hours, e.g., the last 24 hours. A respective
discretized and rolling - i.e., progressively advancing - sequence of time intervals
may be used, to track the up-to-date exposure to sound. To track or monitor the sound
exposure, the cumulative sound exposure could be re-determined from time to time.
[0020] The techniques described herein facilitate determining the CSD based on a discretization
of time domain into the time intervals. It has been found that such a discretization
can adequately reflect the sound exposure and the associated risks to the human hearing
system. For instance, depending on the typical usage cycle of a media-player device,
the discretization could be in the order of days: in such a scenario it can be assumed
that each day also has one or more such periods of rest, e.g., during night time/sleep.
By considering the sound-exposure doses of multiple such time intervals, an averaged
exposure can be considered that inherently takes into consideration stress and counteracting
rest.
[0021] Various techniques are based on the finding that such discretization of the time
domain into the time intervals can lead to quantization artifacts in the tracking
of the sound exposure. In particular, it has been observed that when transitioning
from a preceding time interval into a subsequent time interval, the CSD can be subject
to irregularities such as sudden changes. Such irregularities have been found to originate
from the discretization of time domain into the time intervals. Such irregularities
are observed even if the granularity of the discretization is adjusted, e.g., from
days to hours.
[0022] To mitigate such issues, it is possible to determine the CSD based on a combination
of the sound-exposure doses of multiple time intervals of the discretized and rolling
sequence of time intervals, wherein the combination includes a weighted contribution
of the sound-exposure dose of at least one earliest time interval of the sequence
of time intervals. The sequence of time intervals can be a rolling sequence: i.e.,
the earliest time interval at the beginning of the rolling sequence is removed/discarded
from the sequence once adding a new current time interval at an end of the rolling
sequence. This is sometimes also referred to as a sliding window technique.
[0023] The weighted contribution can correspond to a non-zero weighting factor which defines
a different contribution of the at least one earliest time interval to the CSD if
compared to one or more other time intervals.
[0024] For instance, consider a sequence of eight time intervals, then a non-weighted contribution
would be implemented by the following weighting factors: {1;1;1;1;1;1;1;1;1} - here,
each sound-exposure dose of the various time intervals is weighted with a factor of
"1". A weighted contribution of the single earliest time interval could be implemented
by: {0.5;1;1;1;1;1;1;1;1} - here, the earliest time interval only contributes half
as much to the CSD as the other time intervals; other weighting factors
w are conceivable with 0<w<1. The weighting factor w thus damps the factor of the contribution
associated with the sound-exposure dose of the respective time interval. By combining
a rolling sequence with the weighted contribution of the at least one earliest time
interval, a smoothed fade out of the contribution of the at least one earliest time-interval
of the rolling sequence to the CSD is achieved. This helps to mitigate quantization
effects in the CSD.
[0025] As a general rule, the weighting factor could be time invariant, i.e., not change
as time progresses within a current time interval (dw/dt=0); or the weighting factor
could be time dependent, i.e., change as time progresses within a current time interval
(
w=w
(t))
. For example, the weighting factor can change from 1 to 0 as time progresses from
the beginning of the current time interval to the end of the current time interval.
A weighting factor of 1 can correspond to the sound-exposure dose of the at least
one earliest time interval corresponding in the same manner to the combination that
provides the CSD as another time interval that is not weighted; a weighting factor
smaller than 1 corresponds to damping the respective contribution to the CSD.
[0026] Note that the weighting factor additionally depends on the position of the respective
time interval in the sequence of time intervals. This is expressed using the subscript
k throughout this text:
w =
wk. Here,
k = -N ....0, where
N is the number of time intervals in the sequence, and 0 is the current time interval
including now-time (i.e., the current point in time at which the determination of
the CSD is made). As will be appreciated, the weighting factor is determined based
on the position of the respective time interval in the rolling sequence, i.e., changes
along with the progress in time domain.
[0027] Instead of considering the single earliest time interval, it would also be possible
to use a weighted contribution of the two earliest time intervals, e.g., by {
w-N;
w-N+1; 1; 1; ... . ; 1}, where 0
< w-N < 1, and 0 <
w-N+1 < 1. As a general rule, different earliest time intervals can be damped differently,
i.e.,
w-N ≠
w-N+1 . A gradual fade out would be possible, i.e., sound-exposure doses of earlier time
intervals are damped stronger than sound-exposure doses of later time intervals:
w-N+x <
w-N+y where x<y. This further facilitates the gradual fade-out of earlier time intervals,
e.g., even without requiring a time-dependent weighting factor, by merely considering
the weighting factor that depends on the position of the respective time interval
in the sequence.
[0028] FIG. 1 schematically illustrates aspects with respect to a device 501 that can be
used to implement audio dosimeter functionality according to the various examples
described herein. The device 501 includes a processing circuitry 511, e.g., implemented
by one or more processors, e.g., central processing units, etc.. It would be possible
to employ an application-specific integrated circuit or a field-programmable gate
array. The device 501 also includes a nonvolatile memory 512 that can store program
code. This program code can be loaded and executed by the processing circuitry 511.
Upon executing the program code, the processing circuitry 511 can perform techniques
as described herein, e.g., implement an audio dosimeter. For example, the processing
circuitry 511 could determine sound-exposure doses for multiple time intervals, e.g.,
of a discretized and rolling sequence of time intervals. As a general rule, the sound-exposure
doses described herein could be based on the estimated squared A-weighted and corrected
sound pressure integrated over time (unit "Pa
2h"), see Eq. (0). The correction would normally be a "diffuse-field" correction, which
is in this context a filter used to refer the measured quantity (e.g. in the music
player or at the user's ear) into an equivalent external acoustic field, as would
be the case e.g. when subjected to factory noise. This increases the compatibility
with legacy risk assessment for occupational health. Other implementations of such
correction are possible.
[0029] As illustrated in FIG. 1, the acoustic power can be determined based on a signal
obtained from a microphone 515. Thereby, ambient or in-ear acoustic power can be measured
and integrated over time to form estimates of acoustic energy (sound-exposure doses).
Based on such sound-exposure doses, it would be possible to determine a CSD, e.g.,
by a combination of the sound-exposure doses determined for the multiple time intervals.
In this regard, it is possible to buffer the sound-exposure doses for the time intervals
until determining the CSD; the doses could be buffered in the memory 512.
[0030] It is also possible that the processing circuitry 511 outputs a warning to the user
via a human-machine-interface 514 based on the CSD. As a general rule, it would be
possible to output an acoustic warning or a graphical indication of the warning. For
example, work labor standards in a noise-intensive work environment could be tracked.
[0031] For instance, in the various examples described herein, there may be a predefined
threshold defined in units of the CSD and once the CSD crosses the predefined threshold
from lower values to higher values, the warning is triggered.
[0032] As a general rule, alternatively or additionally to triggering such a warning, it
would also be possible that the acoustic power is adjusted. This can be the case where
an acoustic source can be controlled by the device tracking the CSD. For instance,
it would be possible that certain constraints are imposed on the acoustic power upon
the CSD crossing the predefined threshold. For instance, a maximum value may be imposed
on the acoustic power, e.g., by sending control data to a sound source. Thereby, operation
of the sound source can be tailored to the sound exposure of the user. Continued user-machine
interaction is facilitated.
[0033] FIG. 2 schematically illustrates aspects with respect to a device 502 that can be
used to implement audio dosimeter functionality according to the various examples
described herein. The device 502 generally corresponds to the device 501 as discussed
in connection with FIG. 1. In the scenario of FIG. 2, the device 502 includes a loudspeaker
516 that can be driven by the processing circuitry 511. To that end, the processing
circuitry 511 can include a digital-to-analog converter. The processing circuitry
511 in the scenario of the device 502 can be configured to determine the acoustic
power based on the driver signal provided to the speaker 516 and/or an underlying
audio data.
[0034] Next, details with respect to audio dosimeter functionality that can be provided
by the devices 501, 502 is described in connection with FIG. 3 and FIG. 4.
[0035] FIG. 3 is a flowchart of a method of determining the CSD according to various examples.
For instance, the method of FIG. 3 could be executed by one of the processing circuitries
511 of the devices 501, 502, e.g., upon loading program code from a respective memory
512. FIG. 3 specifically illustrates aspects with respect to determining the CSD based
on sound-exposure doses of multiple time intervals of a rolling sequence. The method
of FIG. 3 can be used to determine the CSD according to prior art techniques, but
also according to techniques disclosed herein.
[0036] At box 3010, it is checked whether a new current time interval is available. Time
domain is discretized into a sequence of time intervals. Once now-time crosses the
boundary of a new time interval (the boundary is defined in accordance with the discretization),
this new time interval is the current time interval.
[0037] Such a sequence 100 is illustrated in FIG. 4. The acoustic power 90 is integrated
over time, resulting in doses in time-discretized intervals 101-109. In the illustrated
example, the time intervals 101-109 all have the same length; but, as a general rule,
it would be possible that different time intervals 101-109 have different lengths
(different lengths could be compensated for when determining the CSD by different
weighting factors that normalize the length). For instance, each time interval 101-109
may correspond to a certain day, e.g., time interval 101 to Monday, time interval
102 to Tuesday, and so forth.
[0038] Continuing with the example using days of the week, wherein the CSD is measured over
the course of a week, in the scenario of FIG. 4: N=6. I.e., the sequence 100 includes
the current time interval and a count of six preceding time intervals, i.e., the sequence
is a weekly rolling time window. For example: considering that the now-time is situated
in the time interval 109 (e.g., Monday): in such a case, the sequence 100 includes
the time intervals 103-109 (e.g., Tuesday to Monday). Differently, for a now-time
situated in the time interval 108 (e.g., Sunday), the sequence 100 includes the time
intervals 102-108 (e.g., Monday to Sunday).
[0039] The sound-exposure doses 111 of all time intervals 101-109 currently included in
the rolling sequence 100 are held in a buffer memory. For example, the sound-exposure
dose of the time interval 103 is "6" (arbitrary units), of the time interval 106 the
sound-exposure dose is "1", for the illustrated example.
[0040] The sound-exposure dose of the current time interval including the now-time is repeatedly
adjusted, by aggregating the acoustic energy over time (this will be explained later
on in connection with FIG. 6). For this reason, the sound-exposure dose 111 is initially
"0", when now-time just crosses the boundary into the time interval 109, i.e., at
point in time T3; the sound-exposure dose 111 of the time interval 109 eventually
increases to "6", towards the end of the time interval 109. This corresponds with
the user's CSD for current time interval increasing over the length of that time interval.
[0041] Now referring again to FIG. 3: Once at box 3010 a new current time interval becomes
available (as the now-time progresses), the rolling sequence 100 of time intervals
is adjusted at box 3020.
[0042] In prior art implementations, the earliest time interval is discarded abruptly (i.e.,
there is no prior damping of the contribution of the respective sound-exposure dose
to the CSD); while according to techniques described herein, the contribution of the
sound-exposure dose of at least one earliest time interval to the CSD is first damped
and only after such damping is the respective at least one earliest time interval
discarded from the sequence. Thus, it can be said that the respective time interval
is faded-out.
[0043] In any case, the sequence 100 is "rolling", i.e., progressing over the course of
time. The associated sound-exposure dose of the then discarded time interval is not
considered in the determining of the CSD, anymore. On the other hand, the sound-exposure
dose of the new current time interval is considered in determining the CSD.
[0044] Differences of box 3020 between prior-art implementations and examples according
to the techniques disclosed herein are summarized in TAB. 1 below:
TAB. 1: Differences in adjusting the sequence between prior art and examples of the
techniques described herein
| Scenario |
How to adjust sequence |
Details |
| A (prior art) |
Earliest time interval discarded abruptly |
There is no fading-out of the earliest time interval. Rather, the earliest time interval
is discarded abruptly, when reaching the earliest position in the sequence. |
| B (example) |
One or more earliest time intervals damped, e.g., progressively faded out |
Prior to completely discarding a time interval of the sequence, the respective contribution
of the sound-exposure dose of that time interval to the CSD is damped if compared
to contributions of other time intervals of the sequence. |
[0045] According to some examples, it would be possible to prolongate the length of the
sequence for scenario B of TAB. 1 if compared to scenario A of TAB. 1: for example,
the sequence length of scenario A may be
N* and the sequence length of scenario B may be
N'=N*+t. where
t>0. The parameter
t could be labeled fade-out overhead. Then, the damping can be implemented for the
t earliest positions in the sequence adjacent to the beginning of the sequence, before
finally discarding the respective time intervals. It is not required in all scenarios
to provide such fade-out overhead; rather, it would be possible to not adjust the
sequence length between scenarios A and B of TAB. 1, and rather implement the fading-out
within the same length of the sequence. Next, at box 3030, the CSD is determined.
This is done based on the sound-exposure doses of the multiple time intervals of the
sequence 100. In some examples, the CSD is determined based on a combination of the
sound-exposure doses of the multiple time intervals currently included in the sequence
100.
[0046] At box 3040, it is checked whether an update of the CSD is required. For instance,
an update could be triggered repeatedly, e.g., every few seconds or minutes or so.
If yes, then box 3010, box 3020 (optionally), and box 3030 are re-executed. A corresponding
iteration 3500 as illustrated in FIG. 3.
[0047] Details with respect to the time-dependent behavior of the CSD 151 is illustrated
in connection with FIG. 5. FIG. 5 is based on the scenario of FIG. 4: FIG. 5 illustrates
the cumulative dose 151 determined for the sequence 100 of FIG. 4 at multiple points
in time T1, T2, T3, and T4.
[0048] More specifically, FIG. 5 illustrates the CSD 151 determined using reference techniques
using a solid line and further illustrates the cumulative dose 151 determined using
techniques described herein using a dotted line.
[0049] It is assumed that for the reference techniques
N=6 with an immediate removal of the earliest time interval, while for the example
techniques
N=7 with a gradual fade-out of the earliest time interval. Thus, considering a now-time
in the time interval 109, the time interval 102 is discarded fully for the reference
techniques, and included in the sequence but considered as a weighted contribution
for the example techniques. For this reason, the time interval 102 is illustrated
using dotted lines in FIG. 4.
[0050] According to the reference techniques, the CSD 151 is determined without applying
a weighted contribution of the at least one earliest time interval; while according
to the techniques described herein, the at least one earliest time interval of the
sequence contributes in a weighted manner to the CSD 151.
[0051] First, the time-dependent behavior of the CSD 151 being determined using reference
techniques is discussed:
At point in time T1, the current time interval is the time interval 108, i.e., the
now-time at point in time T1 is included in the time-interval 108. The sequence 100
includes the time intervals 101-108 (N=6 for the reference techniques). The CSD 151
(determined using reference techniques) at point in time T1 is approximately "20"
(arbitrary units, a.u.) which is the sum of the sound-exposure doses of each one of
the time intervals 101-107, as well as the acoustic energy of the current time interval
108 up to T1.
[0052] More generally, the CSD 151 (determined using reference techniques) can be calculated
as:

where k is an index counting a number of
N previous time intervals and dose
today is the dose of the current time interval, up to and including now-time. For example,
in line with the above example, wherein the current time is time interval 108, at
time T1, dose
today is equal to the dose in time interval 108 up until now-time (T1).
[0053] As time progresses towards T2, the CSD 151 (determined using reference techniques)
increases towards "24", as there is significant acoustic power 90 observed towards
the point in time T2 during the time interval 108 (cf. FIG. 4). Note that from iteration
3500 to iteration 3500 in FIG. 3, as time progresses, the acoustic energy in the current
time interval tends to increase (since more and more acoustic power is aggregated);
accordingly, this effect tends to increase the CSD determined at box 3030.
[0054] Then, at point in time T3, the cumulative dose 151 (determined using reference techniques)
suddenly drops to "16": this is due to the time interval 101 being removed from the
sequence 100, as the new current time interval 109 commences. The sound-exposure dose
111 of the time interval 101 is "8": this contribution to the CSD 151 (determined
using reference techniques) suddenly disappears upon removing the time interval 101.
With time progressing into the time interval 109, the aggregated acoustic energy of
the time interval 109 increases from "0" at the beginning of the time interval 109
to approximately "6" at the end of the time-interval 109 (cf. FIG. 6 below). Accordingly,
the cumulative dose 151 (determined using reference techniques) increases again to
the value of "22", by the end of time interval 109.
[0055] Now considering a scenario in which a warning is triggered each time the threshold
159 is crossed, here corresponding to a CSD of "19": in such a scenario, a warning
would be triggered between points in time T3 and T4, even though the jumps in the
cumulative dose 151 (determined using reference techniques) are not strongly related
to the listening behavior of the user, but rather due to the quantization of the time
domain into the time intervals 101-109.
[0056] For example, the threshold 159 could be defined as follows: a CSD below 1.6 Pa
2h per week is considered safe (this corresponds to <80 dBA for 40 hours). As a general
rule, warnings could be triggered when the dose reaches 100% CSD, 200% CSD, or 300%
CSD, etc. Note: With risk assessment according to the "equal energy principle", a
sound level decrease of 3dB means the exposure time can be doubled, for the same risk.
A sound level decrease of 10dB (perceived as ~half as loud) means the exposure time
can be 10x, for the same risk.
[0057] Such a reference implementation as discussed in connection with FIG. 5 mimics a dosimeter
implementation according to WHO-ITU Safe Listening Devices and Systems/ITU-T H.870
(2018) which utilizes seven memories, one for each day of the week. The weekly dose
= dose as it grows during the current day + the cumulated dose for the 6 preceding
days (N=6). When midnight is passed, the dose saved for the oldest day is reset to
zero. The reset causes an issue with unexpected results for the user and can trigger
unnecessary warnings.
[0058] This problem is mitigated by using a fade-out of the sound-exposure dose of at least
one earliest time interval of the sequence 100 to be discarded, rather than an abrupt
removal from the sequence. The combination of Eq. (1) is modified as follows:

where 0
< w-N < 1 is the weighting factor defining a weighting contribution of the sound-exposure
dose of the earliest time interval to the CSD (the doses for -N+1 to - 1 could be
said to be weighted with "1" or simply non-weighted). Further, to provide for the
fade-out,
N = 6 →
N = 6 + 1 = 7. Here, a fade-out overhead of
t=1 is considered. This is optional, and in other configurations it would be possible
to keep N=6 and rather damp the contribution of the sound-exposure dose of the earliest
time interval within the sequence of length
N=6.
As will be appreciated, this weighted contribution defined by the weighting factor relatively
damps the factor of the sound-exposure dose of the earliest time interval in the sequence.
This corresponds to a fading-out the earliest time interval.
[0059] In some examples, it would be possible that
w-N is fixed, e.g., to 0.5 or another factor. I.e., there is no time dependency. This
may help to reduce a size of quantization drops observed in the CSD.
[0060] In other examples,
w-N may be time dependent,
w-N(
t). For instance, the damping could increase with progression into the current time
interval, e.g., linearly as described by:

where
t denotes the time into the current time interval, i.e.,
t=0 for the now-time at the beginning of the current time interval and
t=l for the now-time at the end of the current time interval, / being the length of the
current time interval. This corresponds to progressively fading-out the earliest time
interval; quantization drops can be avoided.
[0061] Then, for a 24 hour time interval aligned with days (i.e. midnight to midnight),
at noon
w-N(noon) = 0.5 (note: 12/24 hours, 720/1440 minutes = 0.5). Such a behavior is illustrated
for the weighting factor 131 in FIG. 4.
[0062] Thereby, it is possible to smooth or, more specifically, low-pass filter the time
evolution of the CSD 151. Using Eq. (2) and (3), a behavior as indicated by the dotted
line in FIG. 5 can be obtained. Here, the threshold 159 is not crossed and, accordingly,
a warning is not triggered.
[0063] The shape of the CSD 151 according to the dotted line can be qualitatively motivated
as follows: (i) there is a first contribution to the CSD 151 which decreases over
time, namely the contribution of the sound-exposure dose of the earliest time interval
102 which is progressively damped according to Eqs. (2) and (3); (ii) there is a second
contribution to the CSD 151 which tends to increase over time - hence, counteracting
contribution (i): this is the increase in the accumulated acoustic energy in the current
time interval 109. The superposition of contributions (i) and (ii) results in the
illustrated behavior of the CSD 151.
[0064] Instead of such a linear time-dependency of the weighting defining the weighted contribution,
the weighted contribution could generally depend on any predefined time-dependent
filter function. For example, an exponential decay would be conceivable.
[0065] Further, in the example of Eq. (2) and Eq. (3) the sound-exposure dose of the current
time interval is progressively adjusted along with a progression of time into the
current time interval and along with such progressively adjusting, the weighted contribution
depends on a relation between this progression into the current time interval and
a length of the current time interval. It would also be possible that the weighted
contribution depends on a relation between this progression into the current time
interval and the length of the at least one earliest time interval to be discarded
that is respectively weighted.
[0066] Eq. (2) can be rewritten to a more general form:

[0067] wk defines a windowing function. By the weighted contribution of the at least one earliest
time interval (i.e.,
w-N ≠
w0 = 1), the windowing function is asymmetric (while, in reference implementations as
discussed above in connection with Eq. (1), it is rectangular and thus symmetric).
This is helpful, because there is value in a "quick meter response" for the current
day, in order to give feedback to the user about the current listening, while there
is value in a "slow meter response" when it comes to gradually discarding the dose
recorded during the preceding 6-7 days.
[0068] As a general rule, it is possible that the combination to determine the CSD considers
a weighted contribution for only the single earliest time interval at the beginning
of the sequence 100, or for multiple earliest time intervals. Thus, Eq. (2) can be
re-written to

with 1
<M<N.
[0069] For instance, as illustrated in FIG. 4, there can be a subset 141 only including
- e.g., for the now-time at T3 or T4 - the single earliest time interval 102 of the
sequence 100, i.e.,
M=1; or there can be a subset 142 including the two earliest time intervals 102, 103
of the sequence 100 (
M=2). For the latter case of the weighted contribution of multiple earliest time intervals
102, 103, an example weighting factor w 132 as illustrated in FIG. 4, wherein the
dotted line illustrates the time dependency of this weighting factor of 132 for the
sound-exposure dose 111 of the time interval 103 throughout the time progressing into
the current time interval 109, while the full line illustrates a time dependency of
this weighting factor 132 for the sound have an exposure dose 111 of the time interval
102. As illustrated, the relative contribution of the sound-exposure dose 111 of the
time interval 102 to the CSD 151 is smaller than the relative contribution of the
sound-exposure dose 111 of the time interval 103, thereby again defining an asymmetry
in the respective windowing function. As a general rule, the contribution of the sound-exposure
doses associated with different earliest time intervals to the CSD can be damped differently.
A gradual fade out would be possible, i.e., sound-exposure doses of earlier time intervals
are damped stronger than sound-exposure doses of later time intervals:
w-N+x < w-N+y where x<y.
[0070] It may be beneficial to even further smooth the fade-out of the contribution of the
sound-exposure dose of multiple earliest time intervals of the sequence to the CSD.
Above, scenarios have been described in which the fade-out is performed by applying
the weights to the sound-exposure doses of the individual time intervals, cf. Eq.
(2) weight
wk, and weighting factor 132 in FIG. 4. In further examples, it would be possible that
the weighted contribution of multiple earliest time intervals of the sequence 100
is based on an average of these multiple earliest time intervals. By first averaging
sound-exposure doses from several time intervals, e.g., days, their contributions
to the CSD can be evenly distributed the several time intervals and a fade-out is
applied on the CSD:

where
m is sum from several time intervals or the mean from several time intervals, e.g..,

[0071] m can be otherwise based on a combination of the sound-exposure doses of the respective
time intervals.
[0072] FIG. 6 is a flowchart of a method according to various examples. FIG. 6 schematically
illustrates adjusting the sound exposure dose of a current time interval 101-109.
For example, the method of FIG. 6 could be executed by the processing circuitries
511 of the devices 501, 502 (cf. FIG. 1 and FIG. 2).
[0073] FIG. 6 schematically illustrates aspects with respect to progressively adjusting
the sound-exposure dose of the current time interval as time progresses into the current
time interval. By using the method of FIG. 6, the gradual increase of the sound-exposure
dose as illustrated for the time interval 109 in FIG. 4 can be obtained.
[0074] At box 3110, a new time interval is activated, e.g., when crossing a time boundary
between subsequent time intervals. Box 3110 can be aligned with box 3010 of FIG. 3.
[0075] At box 3120, the acoustic energy for a sampling interval is determined. The sampling
interval can be much shorter than the length of the time interval. For example, the
length of the sampling interval can be in the order of seconds or minutes; while the
length of the time interval can be in the order of hours or days. For example, it
would be possible that the duration of the sampling intervals is shorter than the
length of one or more of the time intervals 101-109 at least by a factor of 1000.
[0076] The acoustic energy could be determined using a filter function applied to the acoustic
power, e.g., to consider the digital-to-analog conversion of a loudspeaker driver,
headphone influence, diffuse-field or free-field correction, and/or A-weighting. See
Eq. (0).
[0077] Then, at box 3130, the current sound-exposure dose is adjusted, e.g., by adding the
acoustic energy determined for the current sampling interval to the previously determined
sound-exposure dose (the sound-exposure dose for the time interval can be initialized
at 0 and then progressively be increased with progress into the time interval). This
corresponds to accumulating acoustic energy to determine the sound-exposure dose.
[0078] At box 3140, it is checked whether the current time interval is completed. If not,
then in a further iteration 3600, the acoustic energy is determined for next sampling
interval, by re-executing box 3120 and, subsequently, the sound-exposure dose of the
current time intervals again adjusted. For instance, the iterations 3600 could be
time-aligned with the iterations 3500 (cf. FIG. 3).
[0079] On the other hand, if at box 3140 it is judged that the time interval is completed,
the method commences at box 3150, in which the sound-exposure dose of the current
time interval is concluded, e.g., written to a buffer memory; then, the method commences
by activating a further new time interval at box 3110.
[0080] Summarizing, techniques have been described which help to more accurately trigger
warnings based on tracking sound exposure. Thereby, a user can be influenced towards
more healthy listening habits. The user should be mindful of volume control and listening
time. The user should become educated in what constitutes healthy habits. Relevant
warnings can be issued. By avoiding irrelevant warnings, the severity of any particular
warning is emphasized.
[0081] Further, inaccuracies in the determined CSD can be mitigated, because quantization
effects artificially introducing drops or charms in the CSD can be avoided. Thereby,
misinformation to a user can be avoided.
[0082] When determining a CSD based on the sound-exposure doses of multiple time intervals
(e.g., 7-days), old sound-exposure doses are gradually faded out to avoid unnecessary
fluctuations of the CSD which might, in turn, trigger unnecessary user warnings.
[0083] To illustrate these effects, simulations were performed. FIG. 7 illustrates the acoustic
level over time, for two weeks. In this example, the music level over time was modeled
as a Gaussian random variable. The standard deviation was at first set rather low
at 2 dB to illustrate the situation of consistent listening habits. The listening
hours habit was selected as for a work commuter who is listening on weekdays only
with 2h in the morning and 2h in the evening.
[0084] The basic idea is that users should stay below the weekly reference dose of 100%
CSD (1.6 Pa
2h). If the user hits 100% CSD, a warning is issued and the idea is that users should
now lower the volume control, and stay below 100%. This is illustrated in FIG. 8.
[0085] But the user can also acknowledge the warning and continue without reducing the volume,
accepting the risk, what happens then? According to the implementation example in
H.870 appendix, the dose estimator according to reference implementations may use
seven memories, one for each weekday. This can create quantization effects. E.g.,
when passing midnight between say Tuesday and Wednesday, the old Tuesday memory should
be erased and the current day should increase from zero. This creates sudden jumps
in weekly dose, which can increase the number of warnings. Such quantization effects
are illustrated in FIG. 9, here for lengths of the time intervals corresponding to
one hour and one day. Weekly dose estimates using a method from the present description
is also included ("8d"). As for "d", it uses time intervals corresponding to one day,
but the amount of memories is 8 instead of 7 and a fade is applied to the oldest day.
As will be appreciated, for all lengths, the quantization effects are visible, albeit
less pronounced for shorter lengths. By using a gradual fade-out, quantization effects
can be mitigated.
[0086] Although the invention has been shown and described with respect to certain preferred
embodiments, modifications will occur to others skilled in the art upon the reading
and understanding of the specification. The present invention is limited only by the
scope of the appended claims.
[0087] For illustration, various techniques have been described in the context of sound
exposure and associated sound-exposure doses. As a general rule, similar techniques
may be readily applied to tracking exposure to other environmental quantities, e.g.,
radiation, ultraviolet light, etc.